AI Developer Hybrid
Share
Job Location:
Palo Alto, CA - USA
Monthly Salary:
Not Disclosed
Posted on:
2 hours ago
Vacancies:
1 Vacancy
Job Summary
For further inquiries regarding the following opportunity please contact our Talent Specialist Abdul at or Saravanakumar at
Title: AI Developer - Hybrid
Duration: 6 Months
Location: Palo Alto CA
Duration: 6 Months
Location: Palo Alto CA
Hybrid 3 days onsite a week
Only W2 candidates are eligible for this position. Third-party or C2C candidates will not be considered.
About the Team
- The Enterprise AI team is clients internal AI enablement engine. We evaluate where AI can make a real difference build the platforms and patterns that make adoption easy and help engineering teams across the organization work smarter and faster. We operate at the intersection of applied AI distributed systems and enterprise operations our job is to make client more efficient one AI-powered workflow at a time.
- This is a high-impact high-autonomy team where youll work closely with engineering product and operations teams across client to bring AI capabilities to life.
About the Role
- As an Applied AI Developer on the Enterprise AI team youll evaluate where AI fits build the tools and platforms that make it practical and enable teams across client to adopt modern AI development patterns including LLM orchestration agentic workflows and model governance. You stay hands-on and outcomes-oriented: prototyping evaluating emerging AI technologies and shipping solutions that make the organization measurably more efficient.
What Youll Do
- Think AI-first assess where agentic approaches genuinely outperform conventional solutions then own the quality bar: build automated evals simulation tests and regression frameworks that keep our AI systems reliable and improving as they scale.
- Design agentic systems tool orchestration agent reasoning memory MCP integrations and human-in-the-loop workflows.
- Define and implement AI governance patterns guardrails data lineage auditability and responsible AI practices that ensure our agentic systems are safe compliant and trustworthy.
- Drive adoption through pilots proofs-of-concept and scalable implementations across engineering teams.
- Collaborate with various business functions product security and platform teams to translate AI use cases into production-grade end-to-end solutions.
What Were Looking For
- 5 years of professional software engineering with at least 2 years focused on applied AI in production systems.
- Proficient in Python and/or Go; comfortable reading and writing in the other.
- Proven experience building and scaling multi-agent or agent-driven systems in production real-world operational ownership not just simple LLM workflows.
- Hands-on experience with modern agent ecosystems including frameworks (e.g. LangGraph Google ADK Mastra Claude Agent SDK) observability and evals tooling (e.g. Langfuse LangSmith Braintrust) MCP implementations and leading AI SDKs (e.g. OpenAI Anthropic).
- Strong systems and backend architecture fundamentals designing scalable reliable systems and handling infrastructure performance failure modes cost and deployment concerns.
- Good understanding of cloud-native environments (GCP and/or AWS) compute storage networking and managed AI services.
- Experience designing and integrating with enterprise APIs (REST GraphQL) including authentication and authorization patterns (OAuth2 SAML API keys RBAC). Comfortable working with backend databases (SQL and NoSQL) writing queries understanding data models and building data access layers that enforce role-based access control.
- Strong cross-functional collaborator and communicator able to partner with Product Operations and domain experts to deliver end-to-end systems with measurable real-world impact.
- A force-multiplier on the team you raise the bar for clarity of thinking system design standards and team execution.
Nice to Have
- Experience with AI evaluation tooling (Langfuse LangSmith Braintrust or custom eval frameworks).
- Experience building custom MCP servers not just consuming them.
- Familiarity with containerization and orchestration (Docker Kubernetes).
- AI-native builder with high velocity and ownership intellectual curiosity rapid adoption of new tools bias to action and the ability to drive ambiguous problems from concept to production.
- Hands-on experience with inference cost optimization managing spend as agent deployments scale.
- Experience using AI-powered coding agents (e.g. Claude Code GitHub Copilot Cursor Windsurf) to accelerate development workflows rapid prototyping code generation debugging and test writing.
- Experience with RAG (Retrieval-Augmented Generation) architectures and document retrieval pipelines vector databases embedding models chunking strategies and hybrid search for building agents that answer questions grounded in enterprise documentation.
About us: DivIHN the IT Asset Performance Services organization provides Professional Consulting Custom Projects and Professional Resource Augmentation services to clients in the Mid-West and beyond. The strategic characteristics of the organization are Standardization Specialization and Collaboration. DivIHN is an equal opportunity employer. DivIHN does not and shall not discriminate against any employee or qualified applicant on the basis of race color religion (creed) gender gender expression age national origin (ancestry) disability marital status sexual orientation or military status.
